import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
var =[1,2,3,4,5,6,7]
var_1 =[2,3,4,1,5,6,7]
x_1 = pd.DataFrame({"var":var,"var_1":var_1})
sns.lineplot(x="var",y="var_1",data=x_1)
plt.show()
y_1 = sns.load_dataset("penguins")
y_1
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 339 | Gentoo | Biscoe | NaN | NaN | NaN | NaN | NaN |
| 340 | Gentoo | Biscoe | 46.8 | 14.3 | 215.0 | 4850.0 | Female |
| 341 | Gentoo | Biscoe | 50.4 | 15.7 | 222.0 | 5750.0 | Male |
| 342 | Gentoo | Biscoe | 45.2 | 14.8 | 212.0 | 5200.0 | Female |
| 343 | Gentoo | Biscoe | 49.9 | 16.1 | 213.0 | 5400.0 | Male |
344 rows × 7 columns
sns.lineplot(x="bill_length_mm",y="flipper_length_mm",data=y_1)
plt.show()
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex")
<Axes: xlabel='bill_length_mm', ylabel='bill_depth_mm'>
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex",size=20,style="sex",palette="Accent_r",markers=["o",">"],)
plt.show()
y_1 = sns.load_dataset("penguins").head(20)
y_1
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| 5 | Adelie | Torgersen | 39.3 | 20.6 | 190.0 | 3650.0 | Male |
| 6 | Adelie | Torgersen | 38.9 | 17.8 | 181.0 | 3625.0 | Female |
| 7 | Adelie | Torgersen | 39.2 | 19.6 | 195.0 | 4675.0 | Male |
| 8 | Adelie | Torgersen | 34.1 | 18.1 | 193.0 | 3475.0 | NaN |
| 9 | Adelie | Torgersen | 42.0 | 20.2 | 190.0 | 4250.0 | NaN |
| 10 | Adelie | Torgersen | 37.8 | 17.1 | 186.0 | 3300.0 | NaN |
| 11 | Adelie | Torgersen | 37.8 | 17.3 | 180.0 | 3700.0 | NaN |
| 12 | Adelie | Torgersen | 41.1 | 17.6 | 182.0 | 3200.0 | Female |
| 13 | Adelie | Torgersen | 38.6 | 21.2 | 191.0 | 3800.0 | Male |
| 14 | Adelie | Torgersen | 34.6 | 21.1 | 198.0 | 4400.0 | Male |
| 15 | Adelie | Torgersen | 36.6 | 17.8 | 185.0 | 3700.0 | Female |
| 16 | Adelie | Torgersen | 38.7 | 19.0 | 195.0 | 3450.0 | Female |
| 17 | Adelie | Torgersen | 42.5 | 20.7 | 197.0 | 4500.0 | Male |
| 18 | Adelie | Torgersen | 34.4 | 18.4 | 184.0 | 3325.0 | Female |
| 19 | Adelie | Torgersen | 46.0 | 21.5 | 194.0 | 4200.0 | Male |
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex",size=20,style="sex",palette="Accent_r",markers=["o",">"],
dashes=False)
plt.show()
sns.lineplot(x="bill_length_mm",y="bill_depth_mm",data=y_1,hue="sex",size=20,style="sex",palette="Accent_r",markers=["o",">"],
dashes=False,legend="full")
plt.grid()
plt.title("Nnn")
plt.show()
y_1
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| 5 | Adelie | Torgersen | 39.3 | 20.6 | 190.0 | 3650.0 | Male |
| 6 | Adelie | Torgersen | 38.9 | 17.8 | 181.0 | 3625.0 | Female |
| 7 | Adelie | Torgersen | 39.2 | 19.6 | 195.0 | 4675.0 | Male |
| 8 | Adelie | Torgersen | 34.1 | 18.1 | 193.0 | 3475.0 | NaN |
| 9 | Adelie | Torgersen | 42.0 | 20.2 | 190.0 | 4250.0 | NaN |
| 10 | Adelie | Torgersen | 37.8 | 17.1 | 186.0 | 3300.0 | NaN |
| 11 | Adelie | Torgersen | 37.8 | 17.3 | 180.0 | 3700.0 | NaN |
| 12 | Adelie | Torgersen | 41.1 | 17.6 | 182.0 | 3200.0 | Female |
| 13 | Adelie | Torgersen | 38.6 | 21.2 | 191.0 | 3800.0 | Male |
| 14 | Adelie | Torgersen | 34.6 | 21.1 | 198.0 | 4400.0 | Male |
| 15 | Adelie | Torgersen | 36.6 | 17.8 | 185.0 | 3700.0 | Female |
| 16 | Adelie | Torgersen | 38.7 | 19.0 | 195.0 | 3450.0 | Female |
| 17 | Adelie | Torgersen | 42.5 | 20.7 | 197.0 | 4500.0 | Male |
| 18 | Adelie | Torgersen | 34.4 | 18.4 | 184.0 | 3325.0 | Female |
| 19 | Adelie | Torgersen | 46.0 | 21.5 | 194.0 | 4200.0 | Male |
sns.displot(y_1["flipper_length_mm"])
plt.show()
sns.displot(y_1["flipper_length_mm"],bins=[170,180,190,200,210,220,230,240])
plt.show()
sns.displot(y_1["flipper_length_mm"],kde=True)
plt.show()
y_1.head(20)
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| 5 | Adelie | Torgersen | 39.3 | 20.6 | 190.0 | 3650.0 | Male |
| 6 | Adelie | Torgersen | 38.9 | 17.8 | 181.0 | 3625.0 | Female |
| 7 | Adelie | Torgersen | 39.2 | 19.6 | 195.0 | 4675.0 | Male |
| 8 | Adelie | Torgersen | 34.1 | 18.1 | 193.0 | 3475.0 | NaN |
| 9 | Adelie | Torgersen | 42.0 | 20.2 | 190.0 | 4250.0 | NaN |
| 10 | Adelie | Torgersen | 37.8 | 17.1 | 186.0 | 3300.0 | NaN |
| 11 | Adelie | Torgersen | 37.8 | 17.3 | 180.0 | 3700.0 | NaN |
| 12 | Adelie | Torgersen | 41.1 | 17.6 | 182.0 | 3200.0 | Female |
| 13 | Adelie | Torgersen | 38.6 | 21.2 | 191.0 | 3800.0 | Male |
| 14 | Adelie | Torgersen | 34.6 | 21.1 | 198.0 | 4400.0 | Male |
| 15 | Adelie | Torgersen | 36.6 | 17.8 | 185.0 | 3700.0 | Female |
| 16 | Adelie | Torgersen | 38.7 | 19.0 | 195.0 | 3450.0 | Female |
| 17 | Adelie | Torgersen | 42.5 | 20.7 | 197.0 | 4500.0 | Male |
| 18 | Adelie | Torgersen | 34.4 | 18.4 | 184.0 | 3325.0 | Female |
| 19 | Adelie | Torgersen | 46.0 | 21.5 | 194.0 | 4200.0 | Male |
sns.displot(y_1["flipper_length_mm"],kde=True)
plt.show()
sns.displot(y_1["flipper_length_mm"],kde=True,rug=True,color="m")
plt.show()
sns.displot(y_1["flipper_length_mm"],kde=True,rug=True,color="m",log_scale=True)
plt.show()
y_1 = sns.load_dataset("penguins")
y_1
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 339 | Gentoo | Biscoe | NaN | NaN | NaN | NaN | NaN |
| 340 | Gentoo | Biscoe | 46.8 | 14.3 | 215.0 | 4850.0 | Female |
| 341 | Gentoo | Biscoe | 50.4 | 15.7 | 222.0 | 5750.0 | Male |
| 342 | Gentoo | Biscoe | 45.2 | 14.8 | 212.0 | 5200.0 | Female |
| 343 | Gentoo | Biscoe | 49.9 | 16.1 | 213.0 | 5400.0 | Male |
344 rows × 7 columns
sns.barplot(x=y_1.island,y=y_1.bill_length_mm)
plt.show()
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex")
plt.show()
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1)
plt.show()
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"])
plt.show()
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3)
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\4267160353.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3)
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
orient="v")
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\2636899640.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,color="r")
plt.show()
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
orient="v",palette="Accent")
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\2793013636.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
orient="v",palette="Accent",saturation=0)
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\3405270278.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
orient="v",palette="Accent",errcolor="m",errwidth="5",errorbar="10")
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\4156774541.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
orient="v",palette="Accent",errcolor="m",errwidth="5",errorbar="10",capsize=.2)
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\906675546.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
order_1 =["Biscoe","Dream","Torgersen"]
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
orient="v",palette="Accent",errcolor="m",errwidth="5",errorbar="10",alpha=.5)
plt.show()
C:\Users\Nitin\AppData\Local\Temp\ipykernel_12048\1870751630.py:2: FutureWarning:
The `ci` parameter is deprecated. Use `errorbar=('ci', 92)` for the same effect.
sns.barplot(x="island",y="bill_length_mm",data=y_1,hue="sex",order=order_1,hue_order=["Female","Male"],ci=92,n_boot=3,
y_1
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 339 | Gentoo | Biscoe | NaN | NaN | NaN | NaN | NaN |
| 340 | Gentoo | Biscoe | 46.8 | 14.3 | 215.0 | 4850.0 | Female |
| 341 | Gentoo | Biscoe | 50.4 | 15.7 | 222.0 | 5750.0 | Male |
| 342 | Gentoo | Biscoe | 45.2 | 14.8 | 212.0 | 5200.0 | Female |
| 343 | Gentoo | Biscoe | 49.9 | 16.1 | 213.0 | 5400.0 | Male |
344 rows × 7 columns
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1)
plt.show()
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex")
plt.show()
y_1.head(20)
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | |
|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | Male |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | Female |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | Female |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | Female |
| 5 | Adelie | Torgersen | 39.3 | 20.6 | 190.0 | 3650.0 | Male |
| 6 | Adelie | Torgersen | 38.9 | 17.8 | 181.0 | 3625.0 | Female |
| 7 | Adelie | Torgersen | 39.2 | 19.6 | 195.0 | 4675.0 | Male |
| 8 | Adelie | Torgersen | 34.1 | 18.1 | 193.0 | 3475.0 | NaN |
| 9 | Adelie | Torgersen | 42.0 | 20.2 | 190.0 | 4250.0 | NaN |
| 10 | Adelie | Torgersen | 37.8 | 17.1 | 186.0 | 3300.0 | NaN |
| 11 | Adelie | Torgersen | 37.8 | 17.3 | 180.0 | 3700.0 | NaN |
| 12 | Adelie | Torgersen | 41.1 | 17.6 | 182.0 | 3200.0 | Female |
| 13 | Adelie | Torgersen | 38.6 | 21.2 | 191.0 | 3800.0 | Male |
| 14 | Adelie | Torgersen | 34.6 | 21.1 | 198.0 | 4400.0 | Male |
| 15 | Adelie | Torgersen | 36.6 | 17.8 | 185.0 | 3700.0 | Female |
| 16 | Adelie | Torgersen | 38.7 | 19.0 | 195.0 | 3450.0 | Female |
| 17 | Adelie | Torgersen | 42.5 | 20.7 | 197.0 | 4500.0 | Male |
| 18 | Adelie | Torgersen | 34.4 | 18.4 | 184.0 | 3325.0 | Female |
| 19 | Adelie | Torgersen | 46.0 | 21.5 | 194.0 | 4200.0 | Male |
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",style="sex",size="sex",sizes=(120,40))
y_1
plt.show()
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",style="sex",size="sex",sizes=(120,40)
,palette="Accent")
y_1
plt.show()
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",style="sex",size="sex",sizes=(120,40),
palette="Accent",alpha=.5)
y_1
plt.show()
m = {"Male":"*","Female":"o"}
sns.scatterplot(x="bill_depth_mm",y="bill_length_mm",data=y_1,hue="sex",sizes=(120,40),
markers=m)
plt.show()
data = sns.load_dataset("anagrams").head(10)
data
| subidr | attnr | num1 | num2 | num3 | |
|---|---|---|---|---|---|
| 0 | 1 | divided | 2 | 4.0 | 7 |
| 1 | 2 | divided | 3 | 4.0 | 5 |
| 2 | 3 | divided | 3 | 5.0 | 6 |
| 3 | 4 | divided | 5 | 7.0 | 5 |
| 4 | 5 | divided | 4 | 5.0 | 8 |
| 5 | 6 | divided | 5 | 5.0 | 6 |
| 6 | 7 | divided | 5 | 4.5 | 6 |
| 7 | 8 | divided | 5 | 7.0 | 8 |
| 8 | 9 | divided | 2 | 3.0 | 7 |
| 9 | 10 | divided | 6 | 5.0 | 6 |
data = sns.load_dataset("anagrams")
x=data.drop(columns=["attnr"],axis=1).head(10)
x
| subidr | num1 | num2 | num3 | |
|---|---|---|---|---|
| 0 | 1 | 2 | 4.0 | 7 |
| 1 | 2 | 3 | 4.0 | 5 |
| 2 | 3 | 3 | 5.0 | 6 |
| 3 | 4 | 5 | 7.0 | 5 |
| 4 | 5 | 4 | 5.0 | 8 |
| 5 | 6 | 5 | 5.0 | 6 |
| 6 | 7 | 5 | 4.5 | 6 |
| 7 | 8 | 5 | 7.0 | 8 |
| 8 | 9 | 2 | 3.0 | 7 |
| 9 | 10 | 6 | 5.0 | 6 |
sns.heatmap(x)
plt.show()
sns.heatmap(x,vmin=0,vmax=12)
plt.show()
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr")
plt.show()
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True)
plt.show()
y ={"fontsize":12,"color":"g"}
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True,annot_kws=y,linewidths=10,linecolor="g")
plt.show()
y ={"fontsize":12,"color":"g"}
sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True,annot_kws=y,linewidths=10,linecolor="g",
cbar=False,xticklabels=False,yticklabels=False)
plt.show()
y ={"fontsize":12,"color":"g"}
v =sns.heatmap(x,vmin=0,vmax=12,cmap="PuOr",annot=True,annot_kws=y,linewidths=10,linecolor="g",
cbar=False,xticklabels=False,yticklabels=False)
v.set(xlabel="python",ylabel="NnN")
sns.set(font_scale=1.2)
plt.show()
var = sns.load_dataset("tips")
var
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 239 | 29.03 | 5.92 | Male | No | Sat | Dinner | 3 |
| 240 | 27.18 | 2.00 | Female | Yes | Sat | Dinner | 2 |
| 241 | 22.67 | 2.00 | Male | Yes | Sat | Dinner | 2 |
| 242 | 17.82 | 1.75 | Male | No | Sat | Dinner | 2 |
| 243 | 18.78 | 3.00 | Female | No | Thur | Dinner | 2 |
244 rows × 7 columns
sns.countplot(x="sex",data=var,hue="sex")
plt.show()
sns.countplot(x="sex",data=var,hue="smoker")
plt.show()
sns.countplot(y="sex",data=var,hue="smoker")
plt.show()
sns.countplot(x="sex",data=var,hue="smoker",palette="bwr")
plt.show()
sns.countplot(x="sex",data=var,hue="smoker",palette="bwr",saturation=.6)
plt.show()
var = sns.load_dataset("tips")
var
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 239 | 29.03 | 5.92 | Male | No | Sat | Dinner | 3 |
| 240 | 27.18 | 2.00 | Female | Yes | Sat | Dinner | 2 |
| 241 | 22.67 | 2.00 | Male | Yes | Sat | Dinner | 2 |
| 242 | 17.82 | 1.75 | Male | No | Sat | Dinner | 2 |
| 243 | 18.78 | 3.00 | Female | No | Thur | Dinner | 2 |
244 rows × 7 columns
sns.violinplot(x="day",y="total_bill",data=var)
plt.show()
sns.violinplot(x="day",y="total_bill",data=var)
plt.show()
sns.violinplot(x="day",y="total_bill",data=var,hue="time",linewidth=2,palette="Dark2_r")
plt.show()
sns.violinplot(x="time",y="total_bill",data=var,linewidth=2,palette="Dark2_r",order=["Dinner","Lunch"])
plt.show()
sns.violinplot(x="time",y="tip",data=var,linewidth=2,palette="Dark2_r",order=["Dinner","Lunch"])
plt.show()
sns.violinplot(x="day",y="total_bill",data=var,linewidth=2,saturation=.4,color="r")
plt.show()
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True)
plt.show()
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True,scale="count")
plt.show()
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True,scale="area")
plt.show()
sns.violinplot(x="day",y="total_bill",data=var,hue="sex",split=True,scale="width")
plt.show()
sns.violinplot(x="total_bill",y="day",data=var,hue="sex")
plt.show()
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="quart")
plt.show()
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="point")
plt.show()
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="stick")
plt.show()
sns.violinplot(x="time",y="total_bill",data=var,hue="sex",order=["Dinner","Lunch"],inner="box")
plt.show()
sns.violinplot(x=var["total_bill"])
plt.show()
sns.violinplot(y=var["total_bill"])
plt.show()
sns.pairplot(var)
plt.show()
sns.pairplot(var,hue="sex")
plt.show()
sns.pairplot(var,vars=["tip","total_bill"],hue="sex")
plt.show()
sns.pairplot(var,vars=["tip","total_bill"],hue="sex",hue_order=["Female","Male"])
plt.show()
sns.pairplot(var,vars=["tip","total_bill"],hue="sex",hue_order=["Female","Male"],palette="BuGn")
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],x_vars=["total_bill","tip"])
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],y_vars=["total_bill","tip"])
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="reg")
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="kde")
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="hist")
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="scatter")
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],kind="reg",diag_kind="kde")
plt.show()
sns.pairplot(var,hue="sex",hue_order=["Female","Male"],markers=["*","^"])
plt.show()
var
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 239 | 29.03 | 5.92 | Male | No | Sat | Dinner | 3 |
| 240 | 27.18 | 2.00 | Female | Yes | Sat | Dinner | 2 |
| 241 | 22.67 | 2.00 | Male | Yes | Sat | Dinner | 2 |
| 242 | 17.82 | 1.75 | Male | No | Sat | Dinner | 2 |
| 243 | 18.78 | 3.00 | Female | No | Thur | Dinner | 2 |
244 rows × 7 columns
sns.stripplot(x="day",y="total_bill",data=var)
plt.show()
sns.stripplot(x="day",y="total_bill",data=var,hue="sex")
plt.show()
sns.stripplot(x="day",y="total_bill",data=var,hue="sex",palette="rocket_r",linewidth=1.2,edgecolor="m",jitter=.4,size=4)
plt.show()
m ={"Male":"*","Female":"o"}
sns.stripplot(x="day",y="total_bill",data=var,hue="sex",marker="*")
plt.show()
sns.stripplot(x="day",y="total_bill",data=var,hue="sex",palette="rocket_r",linewidth=1.2,edgecolor="m",jitter=.4,size=4,
alpha=.6)
plt.show()
sns.stripplot(x=var["total_bill"],data=var,hue="sex",marker="*")
plt.show()
sns.stripplot(y=var["total_bill"],data=var,hue="sex",marker="*")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var)
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="time")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="sex")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="sex",color="m")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,hue="sex",color="m",order=["Sun","Sat","Fri","Thur"],showmeans=True)
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="r",order=["Sun","Sat","Fri","Thur"],showmeans=True)
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
meanprops={"marker":"+","markeredgecolor":"r"})
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
meanprops={"marker":"+","markeredgecolor":"r"},linewidth=.3,palette="plasma")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="total_bill",y="day",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
meanprops={"marker":"+","markeredgecolor":"r"},linewidth=.3,palette="plasma")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x="day",y="total_bill",data=var,color="g",order=["Sun","Sat","Fri","Thur"],showmeans=True,
meanprops={"marker":"+","markeredgecolor":"r"},linewidth=.3,palette="plasma",orient="v")
plt.show()
sns.set(style="whitegrid")
sns.boxplot(x=var["total_bill"])
plt.show()
sns.set(style="whitegrid")
sns.boxplot(y=var["total_bill"])
plt.show()
var
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 239 | 29.03 | 5.92 | Male | No | Sat | Dinner | 3 |
| 240 | 27.18 | 2.00 | Female | Yes | Sat | Dinner | 2 |
| 241 | 22.67 | 2.00 | Male | Yes | Sat | Dinner | 2 |
| 242 | 17.82 | 1.75 | Male | No | Sat | Dinner | 2 |
| 243 | 18.78 | 3.00 | Female | No | Thur | Dinner | 2 |
244 rows × 7 columns
sns.catplot(x="size",y="tip",data=var,hue="sex",kind="bar")
plt.show()
sns.catplot(x="size",y="tip",data=var,hue="sex",kind="box")
plt.show()
sns.catplot(x="size",y="tip",data=var,hue="sex",kind="strip")
plt.show()
sns.catplot(x="tip",y="size",data=var,hue="sex",palette="Oranges")
plt.show()
sns.catplot(x="day",y="size",data=var,hue="sex",kind="point",palette="Accent")
plt.show()
sns.catplot(x="day",y="size",data=var,hue="sex",kind="boxen",palette="Accent")
plt.show()
var
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 239 | 29.03 | 5.92 | Male | No | Sat | Dinner | 3 |
| 240 | 27.18 | 2.00 | Female | Yes | Sat | Dinner | 2 |
| 241 | 22.67 | 2.00 | Male | Yes | Sat | Dinner | 2 |
| 242 | 17.82 | 1.75 | Male | No | Sat | Dinner | 2 |
| 243 | 18.78 | 3.00 | Female | No | Thur | Dinner | 2 |
244 rows × 7 columns
sns.set_style("white")
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
sns.set_style("dark")
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
sns.set_style("whitegrid")
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
sns.set_style("darkgrid")
sns.barplot(x="day",y="total_bill",data=var)
plt.show()
sns.set_style("white")
sns.barplot(x="day",y="total_bill",data=var)
sns.despine()
plt.show()
sns.set_style("white")
plt.figure(figsize=(3,2))
sns.barplot(x="day",y="total_bill",data=var)
sns.despine()
plt.show()
sns.set_style("white")
# plt.figure(figsize=(3,2))
sns.set_context("poster",font_scale=1)
sns.barplot(x="day",y="total_bill",data=var)
# sns.despine()
plt.show()
sns.set_style("white")
# plt.figure(figsize=(3,2))
sns.set_context("paper",font_scale=1)
sns.barplot(x="day",y="total_bill",data=var,palette="cool")
# sns.despine()
plt.show()
var
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 239 | 29.03 | 5.92 | Male | No | Sat | Dinner | 3 |
| 240 | 27.18 | 2.00 | Female | Yes | Sat | Dinner | 2 |
| 241 | 22.67 | 2.00 | Male | Yes | Sat | Dinner | 2 |
| 242 | 17.82 | 1.75 | Male | No | Sat | Dinner | 2 |
| 243 | 18.78 | 3.00 | Female | No | Thur | Dinner | 2 |
244 rows × 7 columns
fg=sns.FacetGrid(var,col="sex",hue="day")
fg.map(plt.scatter,"total_bill","tip").add_legend()
plt.show()
fg=sns.FacetGrid(var,col="day",hue="sex")
fg.map(plt.scatter,"total_bill","tip").add_legend()
plt.show()
fg=sns.FacetGrid(var,col="day",hue="sex")
fg.map(plt.bar,"total_bill","tip").add_legend()
plt.show()
fg=sns.FacetGrid(var,col="sex",hue="day",palette="cool")
fg.map(plt.bar,"total_bill","tip").add_legend()
plt.show()
fg=sns.FacetGrid(var,col="sex",hue="day",palette="summer")
fg.map(plt.bar,"total_bill","tip",edgecolor="r").add_legend()
plt.show()